一:sqlserver 執行計劃介紹

　    sqlserver 執行計是在sqlser manager studio 工具中開啟，是檢查一條sql執行效率的工具。建議配合SET STATISTICS IO ON等語句來一起使用，執行計劃是從右向左看，耗時高的一般顯示在右邊,我們知道，sqlserver 查詢資料庫的方式為:

　　1:表掃描(table scan) 查詢速度最慢.

　　2:聚集索引掃描(Clustered Index Scan),按聚集索引逐行進行查詢，效率比表掃描高，但速度還是慢.

　　3:索引掃描（index scan）效率比聚集索引快，根據索引濾出部分資料在進行逐行檢查。

　　4;索引查詢(index seek) 效率比索引掃描還要快，根據索引定位記錄所在位置再取出記錄.

　　5:聚集索引查詢(Clustered Index Seek) 效率最快，直接根據聚集索引獲取記錄。

當發現某個查詢比較慢時，可以首先檢查哪些操作的成本比較高，再看看那些操作在查詢記錄時， 是不是【Table Scan】或者【Clustered Index Scan】，如果確實和這二種操作型別有關，則要考慮增加索引來解決了,sqlser 索引有兩種，聚集索引和非聚集索引，聚集索引是一張表只能有一個，比如id,非聚集索引可以有多個，聚集索引是順序排列的類似於字典查詢拼音a、b、c……和字典文字內容順序是相同的，非聚集索引與內容是非順序排列的，類似字典偏旁查詢時，同一個偏旁‘王’的漢字可能一個在第1頁一個在第5頁。

二：建立測試表

create table shopping_user(uId bigint primary key,uName varchar(10));
create table shopping_goods_category(cId bigint primary key,cName varchar(20));
create table shopping_goods(gId bigint primary key,gName varchar(50),gcId bigint,gPrice int);
create table shopping_order(oId bigint primary key,oUserId bigint,oAddTime datetime,oGoodsId bigint,oMoney int);
　　
 

　　建立測試sql

declare @index int;
set @index = 1;
while(@index<=10)
begin
    insert into shopping_user (uId,uName) values(@index,'user'+cast(@index as varchar(10)));
    set @index = @index+1;
end;

insert into shopping_goods_category (cid,cName) values(1,'水果');
insert into shopping_goods_category (cid,cName) values( 2,'電腦');
insert into shopping_goods_category (cid,cName) values (3,'手機');
insert into shopping_goods_category (cid,cName) values (4,'服裝');
insert into shopping_goods_category (cid,cName) values (5,'食品');

------ 商品表sql

declare @index int;
declare @num int;
set @index = 1;
set @num = 10000;
begin
    while(@index<=100*@num)
    begin
        if @index<=10*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,1,'水果'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end;
        else if @index >10*@num and @index <=20*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,1,'水果'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end;
        else if @index >20*@num and @index <=30*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,2,'電腦'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end;
        else if @index >30*@num and @index <=40*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,2,'電腦'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end;
        else if @index >40*@num and @index <=50*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,3,'手機'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end;
        else if @index >50*@num and @index <=60*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,3,'手機'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end; 
        else if @index >60*@num and @index <=70*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,4,'服裝'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end; 
        else if @index >70*@num and @index <=80*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,4,'服裝'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end; 
        else if @index >80*@num and @index <=90*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,5,'食品'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end; 
        else if @index >90*@num and @index <=100*@num
            begin
                insert into shopping_goods (gId,gcId,gName,gPrice)
                values (@index,5,'食品'+cast (@index as varchar(10)),cast( floor(rand()*100) as int) );
            end; 
        set @index = @index+1;
    end; 
end;


------- 訂單表sql

declare @index int;
declare @num int;
declare @timeNum int;
declare @userId int;
declare @goodsId int; 
declare @money int;
declare @addTime varchar(30);
set @index = 1;
set @num = 10000; 
set @timeNum = 0;
set @userId = 1;
set @goodsid = 1;
set @money = 100;
set @addTime = '';
begin
    while(@index<=100*@num)
    begin
        set @timeNum = cast( floor(rand()*30)+1 as int)
    set @userId = cast( floor(rand()*99)+1 as int)
    set @money = cast ( floor(rand()*5000)[email protected] as int)
    set @addTime = dateadd(day,@timeNum,getdate())
    set @goodsId = cast( floor(rand()*999999)+1 as int)
        if @index<=10*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end;
        else if @index >10*@num and @index <=20*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end;
        else if @index >20*@num and @index <=30*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end;
        else if @index >30*@num and @index <=40*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end;
        else if @index >40*@num and @index <=50*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end;
        else if @index >50*@num and @index <=60*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end; 
        else if @index >60*@num and @index <=70*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end; 
        else if @index >70*@num and @index <=80*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end; 
        else if @index >80*@num and @index <=90*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end; 
        else if @index >90*@num and @index <=100*@num
            begin
                insert into shopping_order (oid,oUserId,oAddTime,oGoodsId,oMoney)
                values (@index,@userId,@addTime,@goodsId,@money );
            end; 
    
    set @index = @index+1;
    end;
    
end;

　　建立索引

create index gcid_index on shopping_goods (gcid);
create index userid_index on shopping_order(ouserid);
create index goodsid_index on shopping_order(ogoodsid);

三：執行計劃分析

　　這裡使用上一篇文章sql語句百萬資料量優化方案中提到的，in和exists來分析,sql語句如下:

SET STATISTICS IO ON

select top 20 * from shopping_order where exists (
select top 10 gid from shopping_goods where gcid =2 and ogoodsid = gid order by gprice desc)

select top 20 * from shopping_order where goodsid in (
select top 10 gid from shopping_goods where gcid =2 order by gprice desc)
 

-- DBCC DROPCLEANBUFFERS 

從上圖中發現，使用exists，開銷最大的是，使用聚集索引查詢，而使用in,第一次操作（從右各左看），就使用了聚集索引掃描，in的效果明顯差。我們再來看聚集索引查詢結果,聚集索引返回的行數是20，見下圖.

然後我們來看使用in查詢，聚集索引掃描，查詢結果卻是20w

接著我們來看使用in查詢，第二個開銷大的排序，從剛才查詢出來的20w資料中，order by desc 返回前20條資料。

此處我們還可以使用SET STATISTICS IO ON來查詢這兩者的io開銷: 

    掃描計數：執行的掃描次數;

    邏輯讀取：從資料快取讀取的頁數;

    物理讀取：從磁碟讀取的頁數;

    預讀：為進行查詢而放入快取的頁數

重要：如果對於一個SQL查詢有多種寫法，那麼這四個值中的邏輯讀(logical reads)決定了哪個是最優化的。

從上圖中發現，exists查詢：shopping_order表掃描次數是2,邏輯讀取是80，shopping_goods表，掃描次數是1，邏輯讀取是6次,

　　　　　　　　　　而in  shopping_order表掃描次數是2,邏輯讀取是55，shopping_goods表，掃描次數是5，邏輯讀取是5247次,當然工作中的sql肯定要複雜得多，但我們可以藉助這個工具來找到需要優化的sql，當然這也只是執行計劃，可能實際執行的效率和這個計劃有出入，但我們還是可以借鑑執行計劃來找到其中的不足。